// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include <stdio.h>
#include <string.h>
#include <sys/ipc.h>
#include <sys/msg.h>
#include <sys/types.h>
#include "paddle/extension.h"

#define MAX_BSZ 256

// #define SAVE_WITH_OUTPUT_DEBUG
struct msgdata {
  long mtype;
  int mtext[MAX_BSZ + 2];  // stop_flag, bsz, tokens
};

// #define SAVE_WITH_OUTPUT_DEBUG
void SaveOutMmsg(const paddle::Tensor &x,
                 const paddle::Tensor &not_need_stop,
                 int64_t rank_id,
                 int msg_queue_id,
                 bool save_each_rank) {
  if (!save_each_rank && rank_id > 0) {
    return;
  }
  auto x_cpu = x.copy_to(paddle::CPUPlace(), false);
  int64_t *x_data = x_cpu.data<int64_t>();
  static struct msgdata msg_sed;

  if (const char *inference_msg_queue_id_env_p =
          std::getenv("INFERENCE_MSG_QUEUE_ID")) {
    std::string inference_msg_queue_id_env_str(inference_msg_queue_id_env_p);
    int inference_msg_queue_id_from_env =
        std::stoi(inference_msg_queue_id_env_str);
    msg_queue_id = inference_msg_queue_id_from_env;
#ifdef SAVE_WITH_OUTPUT_DEBUG
    std::cout << "Your INFERENCE_MSG_QUEUE_ID is: "
              << inference_msg_queue_id_from_env << std::endl;
#endif
  } else {
#ifdef SAVE_WITH_OUTPUT_DEBUG
    std::cout << "Failed to got INFERENCE_MSG_QUEUE_ID at env, use default."
              << std::endl;
#endif
  }
  int inference_msg_id_from_env = 1;
  if (const char *inference_msg_id_env_p = std::getenv("INFERENCE_MSG_ID")) {
    std::string inference_msg_id_env_str(inference_msg_id_env_p);
    inference_msg_id_from_env = std::stoi(inference_msg_id_env_str);
    if (inference_msg_id_from_env == 2) {
      // 2 and -2 is preserve for no-output indication.
      throw std::runtime_error(
          " INFERENCE_MSG_ID cannot be 2, please use other number.");
    }
    if (inference_msg_id_from_env < 0) {
      throw std::runtime_error(
          " INFERENCE_MSG_ID cannot be negative, please use other "
          "number.");
    }

#ifdef SAVE_WITH_OUTPUT_DEBUG
    std::cout << "Your INFERENCE_MSG_ID is: " << inference_msg_id_from_env
              << std::endl;
#endif
  } else {
#ifdef SAVE_WITH_OUTPUT_DEBUG
    std::cout << "Failed to got INFERENCE_MSG_ID at env, use (int)1 as default."
              << std::endl;
#endif
  }
  static key_t key = ftok("/dev/shm", msg_queue_id);

  static int msgid = msgget(key, IPC_CREAT | 0666);
#ifdef SAVE_WITH_OUTPUT_DEBUG
  std::cout << "save_output key: " << key << std::endl;
  std::cout << "save_output msgid: " << msgid << std::endl;
#endif
  msg_sed.mtype = 1;
  bool not_need_stop_data = not_need_stop.data<bool>()[0];
  // printf("not_need_stop_data %d\n", (int)not_need_stop_data);
  msg_sed.mtext[0] = not_need_stop_data ? inference_msg_id_from_env
                                        : -inference_msg_id_from_env;
  int bsz = x.shape()[0];
  msg_sed.mtext[1] = bsz;
  for (int i = 2; i < bsz + 2; i++) {
    msg_sed.mtext[i] = (int)x_data[i - 2];
  }
#ifdef SAVE_WITH_OUTPUT_DEBUG
  std::cout << "save_output msg data: ";
  for (int i = 0; i < bsz; i++) {
    std::cout << " " << (int)x_data[i];
  }
  std::cout << std::endl;
#endif
  if ((msgsnd(msgid, &msg_sed, (MAX_BSZ + 2) * 4, 0)) == -1) {
    printf("save_output full msg buffer\n");
  }
  return;
}

void SaveOutMmsgStatic(const paddle::Tensor &x,
                       const paddle::Tensor &not_need_stop,
                       int64_t rank_id,
                       bool save_each_rank) {
  SaveOutMmsg(x, not_need_stop, rank_id, 1, save_each_rank);
}

void SaveOutMmsgDynamic(const paddle::Tensor &x,
                        const paddle::Tensor &not_need_stop,
                        int64_t rank_id,
                        int msg_queue_id,
                        bool save_each_rank) {
  SaveOutMmsg(x, not_need_stop, rank_id, msg_queue_id, save_each_rank);
}

PD_BUILD_OP(save_output)
    .Inputs({"x", "not_need_stop"})
    .Attrs({"rank_id: int64_t", "save_each_rank: bool"})
    .Outputs({"x_out"})
    .SetInplaceMap({{"x", "x_out"}})
    .SetKernelFn(PD_KERNEL(SaveOutMmsgStatic));

PD_BUILD_OP(save_output_dynamic)
    .Inputs({"x", "not_need_stop"})
    .Attrs({"rank_id: int64_t", "msg_queue_id: int", "save_each_rank: bool"})
    .Outputs({"x_out"})
    .SetInplaceMap({{"x", "x_out"}})
    .SetKernelFn(PD_KERNEL(SaveOutMmsgDynamic));
